Using neural networks for fault detection in a distillation column
by I. Manssouri, Y. Chetouani, B. El Kihel
International Journal of Computer Applications in Technology (IJCAT), Vol. 32, No. 3, 2008

Abstract: Several methods of fault detection have been put to testing with the purpose of securing the installations and reducing the risks of accidents. This paper presents a new approach of fault detection based on the realisation of a Bayesian neural separate at radial basis functions. In this paper, our contribution consists of demonstrating the way this kind of network can be used as faults separate, applied to a continuous distillation column containing a binary mixture of toluene/methylcyclohexane. The latter is carried out through the use of test base containing two operating modes: normal and abnormal.

Online publication date: Sun, 26-Oct-2008

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